SKA is a tool for comparing small and highly similar genomes using split k-mers. This guide explains how to create a SNP alignment from a skf file using the different options implemented in the command ska align (here using ska v0.3.5).

Recommended command line

For those in a hurry, the recommended command line for filtering for precise SNP calling is:

ska align --no-gap-only-sites --filter-ambig-as-missing --filter no-ambig-or-const

Breakdown using an example

In this example, let’s consider a skf file generated using k=51 from Illumina sequencing reads of 45 Mycobacterium tuberculosis isolates collected by the UKHSA, and belonging to the same transmission cluster (i.e. less than 12 SNPs between isolates).

Using the default command ska align, SKA creates a SNP alignment containing 262,123 positions. This is because SKA considers by default the absence of a split k-mer as a potential evolutionary event, and any split k-mer absent in at least one sample will be output.

Some of these samples have quite low coverage, causing k-mers to be erroneously missing. So, we can ask SKA not to output split k-mers differing solely by the presence of missing data (i.e. without any SNP variation) using the command ska align --no-gap-only-sites. In this case, the SNP alignment is reduced to 181 positions.

This alignment still contains many positions with a large fraction of ambiguous characters. In Mtb, these positions likely correspond to split k-mers with different middle-bases duplicated in the genome. Variations in coverage between samples mean that in some cases only one of the duplicated split k-mer will be present in the skf file, potentially leading to spurious variation between isolates.

As these are largely due to repeats, to remove these positions, we can ask SKA to consider all ambiguous characters as missing data by adding --filter-ambig-as-missing. In this case, split k-mers containing a lot of ambiguous characters will be seen as filled with missing data and discarded by the --min-freq parameter (0.1 by default), producing an alignment of 154 SNPs.

Finally, this alignment still contains lot of positions differing solely by the presence of an ambiguous character. These variants might be real: e.g. SNP in a duplicated split k-mer with same middle-base or intra-isolate polymorphism. They may also be the result of errors: e.g. split k-mer introduced by contamination, unfiltered sequencing errors in high coverage samples, split k-mer introduced by more complex variants.

We can also remove these variants by asking SKA to only output split k-mers with unambiguous ATGC variations by adding --filter no-ambig-or-const. This produces an alignment of 81 SNPs, identical to those obtained by reference-based read-alignment pipelines.

Hopefully this brief overview gave you a good understanding of ska align’s filtering options.